- Teacher: Dr. Md. Fokhray Hossain
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Software Testing and Quality Assurance
The course will be suitable for learners who have entered tertiary level of education and have to study through the medium of English, but are not skilled enough to meet the demands of academic reading and writing. The course will help learners attain study skills necessary for studying in English. There will be focus on reading academic texts and writing for academic purposes. Students will also learn to effectively use written communication in a professional setting. The course will also orient learners with IELTS General Training/ Academic Module.
Discrete mathematics is a branch of mathematics that deals with finite and discrete objects, such as integers, sets, graphs, logic, and algorithms. It is often used as a foundation for computer science, software engineering, cryptography, data science, and other fields that involve computation and information. In this course the following topics will be covered: Logic and proofs: how to use symbols, truth tables, and rules of inference to reason about propositions, predicates, and quantifiers. Sets and functions: how to define, manipulate, and compare sets, relations, functions, and cardinality. Number theory and cryptography: how to use modular arithmetic, divisibility, prime numbers, and congruences to encrypt and decrypt messages, and to test the security of cryptographic schemes. Combinatorics and probability: how to count and enumerate objects, permutations, combinations, binomial coefficients, and apply the principles of inclusion-exclusion, pigeonhole, and induction. Recursion and recurrence relations: how to define and solve problems that involve recursive definitions, such as Fibonacci numbers, factorial, and Tower of Hanoi. Graph theory and algorithms: how to represent, traverse, and analyze graphs, trees, networks, and their properties, such as connectivity, coloring, Eulerian and Hamiltonian paths, and planarity. Computability and complexity: how to classify problems and algorithms according to their decidability, solvability, and efficiency, using concepts such as Turing machines, halting problems, NP-completeness, and big-O notation.